Swing Algo V1.3
An upgrade of Swing Algo V1.2 to reduce chop heavily, used for trading ETH. For differences to other versions, see below.
This indicator can be used for e.g. swing algorithmic trading. It will give Buy/Long and Sell/Short signals on the chart. This algorithm uses a combination of several (custom) functions and rules to find good entry points for trend trading. After many iterations and tests I came up with this particular setup, which is highly optimized for the ETH/USD trading pair on the daily (D) timeframe. Attention was also paid to stability, as all parameters are set onto plateaus, so that smaller changes in the characteristic price action should not affect the efficiancy too much. For other assets and/or timeframes it is however possible to change algorithmic parameters within the indicator settings to tune this swing algorithm. You don't need any programming skills or similar abilities to navigate this indicator.
For the here presented backtest data, we omitted the biggest portion of the cryptocurrency bullrun in 2017 (starting only at 1st July 2017) so that the results become more realistic for long-term swing traders (investing at least 2-3 years into trading) if such large runs do not happen again. As cryptocurrencies like Ethereum are still to this date capable of doing comparatively smaller runs of about 2-3x in a few weeks/months (as witnessed in 2020), the order of magnitude of the shown results is still realistic for long-term trend trading efforts. Do not expect these results in a matter of days or weeks, and of course as with any trading strategy past performances are not indicative of future results.
Within this indicator you can choose the backtest time interval to test the perfomance of this algorithm for different time windows and different trading pairs. Here various backtesting parameters (e.g. trading fees) can be customized. Default settings for the shown backtest are a starting balance of $1000, a slippage of 2 ticks (= $0.02) and a trading fee of 0.26 % (which is the worst taker fee on the Kraken exchange) to have realistic settings. However as we do not conduct many trades with this strategy, fees should not impact our performance too much. As long-term swing traders, we devote one initial portion of our portfolio to swing trading and from then on always use 100% of this portion for the next trade to get the compounding starting. This is in difference to other trading styles which use various, often very small, percentage values for their short- or mid-term trades. Keep this in mind when evaluating the backtest data. Also note that due to the small number of trades the statistical significance is low. It is not possible to gather an abundance of long-term trend signals in the order of hundreds or thousands trades, as much more time would have to pass for this in the case of rather new assets like Ethereum.
Additionally to the TradingView Strategy Tester you can also plot your equity directly on the chart to get a sense for the performance. For this you can also scale the equity graph to e.g. match the starting point of your equity with some price point on the chart to get a direct comparison to 'Buy & Hold' strategies over time.
This indicator (and all other content I provide) is no financial advice. If you use this indicator you agree to my Terms and Conditions which can be found on my Twitter profile linked on my TradingView profile or in my signature.
Differences to other versions:
- Changed from a dual (V1, V1.1) to a single smoothing function system (V1.2, V1.3), which can react better to more sudden price movements that got prevalent during the current end-phase of the stock bullmarket due to correlations, while still handling 'normal' price action well
- Changed the oscillator part of the algorithm again with one that handles chop for the ETH/USD trading pair extremely well.
- Improved net profits by potentially +100% in comparison to V1 for ETH/USD on daily timeframe
- However for other assets (e.g. BTC and smaller coins like XTZ and ALGO) and timeframes V1 might perform better than V1.3 due to somewhat different characteristic price action. I leave you with all options to play so that you can find the best solution for a given trading pair.
- There's also a previous version called Swing Algo V1.2 considered the go-to algo at the moment, which works similar to V1.3, but operates a bit less tight, leading to more flexibility while suppressing chop not as much as V1.3.
For access please contact me via DM on TradingView or on Twitter (linked on my TradingView profile and my signature). People who purchased access to any 'Swing Algo 1.x' get access to all other 'Swing Algo V1.x' indicators automatically ('Swing Algo V1' counts as 'Swing Algo V1.0').
This indicator can be used for e.g. swing algorithmic trading. It will give Buy/Long and Sell/Short signals on the chart. This algorithm uses a combination of several (custom) functions and rules to find good entry points for trend trading. After many iterations and tests I came up with this particular setup, which is highly optimized for the ETH/USD trading pair on the daily (D) timeframe. Attention was also paid to stability, as all parameters are set onto plateaus, so that smaller changes in the characteristic price action should not affect the efficiancy too much. For other assets and/or timeframes it is however possible to change algorithmic parameters within the indicator settings to tune this swing algorithm. You don't need any programming skills or similar abilities to navigate this indicator.
For the here presented backtest data, we omitted the biggest portion of the cryptocurrency bullrun in 2017 (starting only at 1st July 2017) so that the results become more realistic for long-term swing traders (investing at least 2-3 years into trading) if such large runs do not happen again. As cryptocurrencies like Ethereum are still to this date capable of doing comparatively smaller runs of about 2-3x in a few weeks/months (as witnessed in 2020), the order of magnitude of the shown results is still realistic for long-term trend trading efforts. Do not expect these results in a matter of days or weeks, and of course as with any trading strategy past performances are not indicative of future results.
Within this indicator you can choose the backtest time interval to test the perfomance of this algorithm for different time windows and different trading pairs. Here various backtesting parameters (e.g. trading fees) can be customized. Default settings for the shown backtest are a starting balance of $1000, a slippage of 2 ticks (= $0.02) and a trading fee of 0.26 % (which is the worst taker fee on the Kraken exchange) to have realistic settings. However as we do not conduct many trades with this strategy, fees should not impact our performance too much. As long-term swing traders, we devote one initial portion of our portfolio to swing trading and from then on always use 100% of this portion for the next trade to get the compounding starting. This is in difference to other trading styles which use various, often very small, percentage values for their short- or mid-term trades. Keep this in mind when evaluating the backtest data. Also note that due to the small number of trades the statistical significance is low. It is not possible to gather an abundance of long-term trend signals in the order of hundreds or thousands trades, as much more time would have to pass for this in the case of rather new assets like Ethereum.
Additionally to the TradingView Strategy Tester you can also plot your equity directly on the chart to get a sense for the performance. For this you can also scale the equity graph to e.g. match the starting point of your equity with some price point on the chart to get a direct comparison to 'Buy & Hold' strategies over time.
This indicator (and all other content I provide) is no financial advice. If you use this indicator you agree to my Terms and Conditions which can be found on my Twitter profile linked on my TradingView profile or in my signature.
Differences to other versions:
- Changed from a dual (V1, V1.1) to a single smoothing function system (V1.2, V1.3), which can react better to more sudden price movements that got prevalent during the current end-phase of the stock bullmarket due to correlations, while still handling 'normal' price action well
- Changed the oscillator part of the algorithm again with one that handles chop for the ETH/USD trading pair extremely well.
- Improved net profits by potentially +100% in comparison to V1 for ETH/USD on daily timeframe
- However for other assets (e.g. BTC and smaller coins like XTZ and ALGO) and timeframes V1 might perform better than V1.3 due to somewhat different characteristic price action. I leave you with all options to play so that you can find the best solution for a given trading pair.
- There's also a previous version called Swing Algo V1.2 considered the go-to algo at the moment, which works similar to V1.3, but operates a bit less tight, leading to more flexibility while suppressing chop not as much as V1.3.
For access please contact me via DM on TradingView or on Twitter (linked on my TradingView profile and my signature). People who purchased access to any 'Swing Algo 1.x' get access to all other 'Swing Algo V1.x' indicators automatically ('Swing Algo V1' counts as 'Swing Algo V1.0').
Phát hành các Ghi chú:
First iterative parameter update for Swing Algo V1.3 after 20 months of forward testing, to increase the signal filtering during noisy periods (chop) to some degree.
Phát hành các Ghi chú:
Slight modification of the oscillator part of the algorithm, and second iterative parameter update to adjust the signal filtering.
Website (for access to my scripts): deantrader.com
Twitter (for Swing Algo footage): twitter.com/Dean_Trader
Twitter (for Swing Algo footage): twitter.com/Dean_Trader